Table of Contents

  • 1  Installing Basemap package
  • 2  Adding vector layers to a map
  • 3  Projection, bounding box, & resolution
    • 3.1  Mercator Projection
    • 3.2  Cylindrical Equidistant Projection
    • 3.3  Orthographic Projection
    • 3.4  Robinson Projection
  • 4  Plotting a specific region
  • 5  Background relief maps
    • 5.1  Draw land-sea mask image
    • 5.2  NASA Blue Marble image
    • 5.3  Shaded relief image
    • 5.4  NOAAetopo relief image
  • 6  Plotting netCDF data using Basemap
    • 6.1  Reading ECMWF temperature data
    • 6.2  Plotting filled contour maps
    • 6.3  Plotting contour maps
    • 6.4  Plotting pseudo color maps
    • 6.5  Plot data points
In [1]:
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap

  • Basemap is a matplotlib extension used to visualize and create geographical maps in python.

  • If you need further information on basemap, please visit basemap page: https://matplotlib.org/basemap/index.html

Installing Basemap package¶

conda install -c anaconda basemap

In [2]:
# Import the Basemap and Matplotlib libraries:

from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt

Adding vector layers to a map¶

Coastlines

  • First, let’s initialize a map with Basemap() function

  • Then, use the drawcoastlines() function to add coastlines on the map

In [3]:
fig = plt.figure(figsize = (8,8)) 
m = Basemap()
m.drawcoastlines()
plt.title("Coastlines", fontsize=20)
plt.show()

  • drawcoastlines function has the following main arguments:

  • linewidth: 1.0, 2.0, 3.0…

  • linestyle: solid, dashed…

  • color: black, red…

In [4]:
fig = plt.figure(figsize = (6,6))
m = Basemap()
m.drawcoastlines(linewidth=1.0, linestyle='dashed', color='red')
plt.title("Coastlines", fontsize=20)
plt.show()

Countries

  • Use the drawcountries() function to add countries on the map
In [5]:
fig = plt.figure(figsize = (8,8))
m = Basemap()
m.drawcoastlines(linewidth=1.0, linestyle='solid', color='black')
m.drawcountries()
plt.title("Country boundaries", fontsize=20)
plt.show()
In [6]:
fig = plt.figure(figsize = (12,12))
m = Basemap()
m.drawcoastlines(linewidth=1.0, linestyle='solid', color='black')
m.drawcountries(linewidth=1.0, linestyle='solid', color='r')
plt.title("Country boundaries", fontsize=20)
plt.show()

Draw major rivers

  • Use the drawrivers() function to add major rivers on the map.

  • drawrivers() function can take linewidth, linestyle, and color arguments

In [7]:
fig = plt.figure(figsize = (12,12))
m = Basemap()
m.drawcoastlines(linewidth=1.0, linestyle='solid', color='black')
m.drawcountries(linewidth=1.0, linestyle='solid', color='k')
m.drawrivers(linewidth=0.5, linestyle='solid', color='#0000ff')
plt.title("Major rivers", fontsize=20)
plt.show()

Fill continents

  • This function is used to draw color filled continents

  • Use fillcontinents() function to fill continents

In [8]:
fig = plt.figure(figsize = (8,8))
m = Basemap()
m.drawcoastlines(linewidth=1.0, linestyle='solid', color='black')
m.drawcountries(linewidth=1.0, linestyle='solid', color='k')
m.fillcontinents()
plt.title("Color filled continents", fontsize=20)
plt.show()

The fillcontinents() function can take the following arguments:

  • color: fills continents (default gray)

  • lake_color: fills inland lakes

  • alpha: sets transparency for continents

In [9]:
fig = plt.figure(figsize = (12,12))
m = Basemap()
m.drawcoastlines(linewidth=1.0, linestyle='solid', color='black')
m.drawcountries(linewidth=1.0, linestyle='solid', color='k')
m.fillcontinents(color='coral',lake_color='aqua', alpha=0.9)
plt.title("Color filled continents", fontsize=20)
plt.show()

Draw map boundary

  • The drawmapboundary() function is used to draw the earth boundary on the map.

  • drawmapboundary() function can take the following arguments:

    • linewidth: sets line width for boundary line (default: 1)

    • color: sets the color of the boundary line (default: black)

    • fill_color: fills the map background region

In [10]:
fig = plt.figure(figsize = (6,6))
m = Basemap()
m.drawcoastlines(linewidth=1.0, linestyle='solid', color='black')
m.drawcountries(linewidth=1.0, linestyle='solid', color='k')
m.fillcontinents(color='coral',lake_color='aqua')
m.drawmapboundary(color='b', linewidth=2.0, fill_color='aqua')
plt.title("Filled map boundary", fontsize=20)
plt.show()

Draw and label longitude lines

  • drawmeridians() function is used to draw & label meridians/longitude lines

  • drawmeridians()function can take the following arguments:

    • List of longitude values created with range() for integer values & np.arange() for floats values.

  • color: sets the color of the line longitude lines (default: black).

  • textcolor: sets the color of labels (default: black)

  • linewidth: sets the line width for the longitude lines

  • dashes: sets the dash pattern for the longitude lines (default: [1,1])

  • labels: sets the label’s position with four values [0,0,0,0] representing left, right, top, & bottom. Change these values to 1 where you want the labels to appear.

In [11]:
fig = plt.figure(figsize = (8,8))
m = Basemap()
m.drawcoastlines(linewidth=1.0, linestyle='solid', color='black')
m.drawcountries(linewidth=1.0, linestyle='solid', color='k')
m.fillcontinents(color='coral',lake_color='aqua')
m.drawmeridians(range(0, 360, 30), color='k', linewidth=1.0, dashes=[4, 4], labels=[1, 0, 0, 1])
plt.title("Longitude lines", fontsize=20, pad=30)
plt.show()

Draw and label latitude lines

  • drawparallels() function is used to draw & label parallels/latitude lines.

  • drawparallels()function uses similar arguments like drawmeridians()

In [12]:
fig = plt.figure(figsize = (8,8))
m = Basemap()
m.drawcoastlines(linewidth=1.0, linestyle='solid', color='black')
m.drawcountries(linewidth=1.0, linestyle='solid', color='k')
m.fillcontinents(color='coral',lake_color='aqua')
m.drawparallels(range(-90, 100, 20), color='k', linewidth=1.0, dashes=[4, 4], labels=[1, 1, 0, 0])
plt.title("Latitude lines", fontsize=20)
plt.show()

Let's put the drawmeridians and drawparallels functions together

In [13]:
fig = plt.figure(figsize = (12,12))
m = Basemap()
m.drawcoastlines(linewidth=1.0, linestyle='solid', color='black')
m.drawcountries(linewidth=1.0, linestyle='solid', color='k')
m.fillcontinents(color='coral',lake_color='aqua')
m.drawmeridians(range(0, 360, 20), color='k', linewidth=1.0, dashes=[4, 4], labels=[0, 0, 0, 1])
m.drawparallels(range(-90, 100, 10), color='k', linewidth=1.0, dashes=[4, 4], labels=[1, 0, 0, 0])
plt.ylabel("Latitude", fontsize=15, labelpad=35)
plt.xlabel("Longitude", fontsize=15, labelpad=20)
plt.show()

Projection, bounding box, & resolution¶

Projection, bounding box, & resolution

  • Basemap() function is used to set projection, bounding box, & resolution of a map

Map projection:

  • Inside the Basemap() function, the projection=" argument can take several pre-defined projections

  • To specify the desired projection, use the general syntax shown below:

m = Basemap(projection='aeqd')
m = Basemap(projection='cyl')

| Projection name | Basemap syntax | | Projection name | Basemap syntax | |----------------------------------- |---------------- |--- |----------------------------------- |---------------- | | Equidistant Conic | eqdc | | Cylindrical Equal Area | cea | | Miller Cylindrical | mill | | McBryde-Thomas Flat-Polar Quartic | mbtfpq | | Mercator | merc | | Azimuthal Equidistant | aeqd | | Stereographic | stere | | Sinusoidal | sinu | | Polyconic | poly | | Rotated Pole | rotpole | | Oblique Mercator | omerc | | Cylindrical Equidistant | cyl | | Gnomonic | gnom | | North-Polar Stereographic | npstere | | Mollweide | moll | | South-Polar Stereographic | spstere | | Lambert Conformal | lcc | | Hammer | hammer | | Transverse Mercator | tmerc | | Geostationary | geos | | North-Polar Lambert Azimuthal | nplaea | | Near-Sided Perspective | nsper | | Gall Stereographic Cylindrical | gall | | Eckert IV | eck4 | | North-Polar Azimuthal Equidistant | npaeqd | | Albers Equal Area | aea | | Kavrayskiy VII | kav7 | | South-Polar Azimuthal Equidistant | spaeqd | | Orthographic | ortho | | Cassini-Soldner | cass | | van der Grinten | vandg | | Lambert Azimuthal Equal Area | laea | | South-Polar Lambert Azimuthal | splaea | | Robinson | robin |

Some projections require setting bounding box, map center, & map size of the map using the following arguments:

a) Bounding box/map corners:

llcrnrlat: lower-left corner geographical latitude
urcrnrlat: upper-right corner geographical latitude
llcrnrlon: lower-left corner geographical longitude
urcrnrlon: upper-right corner geographical longitude

Example:

m = Basemap(projection='cyl', ,llcrnrlat=-80,urcrnrlat=80,llcrnrlon=-180,urcrnrlon=180)

b) Map center:

lon_0: central longitude
lat_0: central latitude

Example:

m = Basemap(projection='ortho', lon_0 = 25, lat_0 = 10)

c) Map resolution: The map resolution argument determines the quality of vector layers such as coastlines, lakes, & rivers etc.

The available options are:

  • c: crude
  • l: low
  • i: intermediate
  • h: high
  • f: full

pip install basemap-data-hires

conda install -c conda-forge basemap-data-hires

Mercator Projection¶

In [14]:
# Create a global map with a Mercator Projection

fig = plt.figure(figsize = (8,8))
m = Basemap(projection='merc',llcrnrlat=-80,urcrnrlat=80,llcrnrlon=-180,urcrnrlon=180)
m.drawcoastlines()
m.fillcontinents(color='tan',lake_color='lightblue')
m.drawcountries(linewidth=1, linestyle='solid', color='k' ) 
m.drawmapboundary(fill_color='lightblue')
plt.title("Mercator Projection", fontsize=20)
Out[14]:
Text(0.5, 1.0, 'Mercator Projection')

Cylindrical Equidistant Projection¶

In [15]:
# Create a global map with a Cylindrical Equidistant Projection

fig = plt.figure(figsize = (8,8))
m = Basemap(projection='cyl',llcrnrlat=-80,urcrnrlat=80,llcrnrlon=-180,urcrnrlon=180)
m.drawcoastlines()
m.fillcontinents(color='tan',lake_color='lightblue')
m.drawcountries(linewidth=1, linestyle='solid', color='k' ) 
m.drawmapboundary(fill_color='lightblue')
plt.title(" Cylindrical Equidistant Projection", fontsize=20)
Out[15]:
Text(0.5, 1.0, ' Cylindrical Equidistant Projection')

Orthographic Projection¶

In [16]:
# Create a global map with Orthographic Projection

fig = plt.figure(figsize = (4,4))
m = Basemap(projection='ortho', lon_0 = 25, lat_0 = 10)
m.drawcoastlines()
m.fillcontinents(color='tan',lake_color='lightblue')
m.drawcountries(linewidth=1, linestyle='solid', color='k' ) 
m.drawmapboundary(fill_color='lightblue')
plt.title("Orthographic Projection", fontsize=18)
Out[16]:
Text(0.5, 1.0, 'Orthographic Projection')

Robinson Projection¶

In [17]:
# Create a global map with a Robinson Projection

fig = plt.figure(figsize = (8,8))
m = Basemap(projection='robin',llcrnrlat=-80,urcrnrlat=80,llcrnrlon=-180,urcrnrlon=180, lon_0 = 0, lat_0 = 0)
m.drawcoastlines()
m.fillcontinents(color='tan',lake_color='lightblue')
m.drawcountries(linewidth=1, linestyle='solid', color='k' ) 
m.drawmapboundary(fill_color='lightblue')
plt.title(" Robinson Projection", fontsize=20)
Out[17]:
Text(0.5, 1.0, ' Robinson Projection')

Plotting a specific region¶

  • By passing bounding box information (llcrnrlon, llcrnrlat, urcrnrlon,urcrnrlat)
In [18]:
fig = plt.figure(figsize = (8,8))
m = Basemap(projection='cyl',llcrnrlon=32.5,llcrnrlat=3,urcrnrlon=49,urcrnrlat=15, resolution = 'l')
m.drawcoastlines()
m.fillcontinents(color='tan',lake_color='lightblue')
m.drawcountries(linewidth=1, linestyle='solid', color='k' ) 
m.drawmapboundary(fill_color='lightblue')
m.drawcoastlines()
plt.show()

b) By passing the central longitude & central latitude, as well as the width, & height values.

  • Here, the width and height are given in meters.
In [19]:
fig = plt.figure(num=None, figsize=(8, 8) ) 
m = Basemap(projection='aea', width=1700000, height=1500000, resolution='l',lon_0= 40.5,lat_0=8.7)
m.fillcontinents(color='tan',lake_color='aqua')
m.drawmapboundary(fill_color='lightblue')
m.drawcountries(linewidth=1, linestyle='solid', color='k' )
m.drawcoastlines()
plt.show()

Background relief maps¶

Basemap provides several background relief images including:

a) Land-sea mask image
b) NASA blue marble
c) NOAA etopo
d) Shaded relief

Draw land-sea mask image¶

drawlsmask() function used to draw lakes, land, & oceans at once.

  • It avoids fillcontinents & drawmapboundary functions.

  • drawlsmask() function can take the following arguments:

    • land_color: sets the color of the land (by default it’s gray)

    • ocean_color: sets the color of the oceans (by default it’s white)

    • resolution: sets the coastline resolution (by default it’s l, you can change it to: c, l, i , h, or f )

    • lakes: plots lakes & ponds (by it default it’s True)

    • grid: sets the land/sea mask grid spacing in minutes (by default it’s 5; You can change it to: 10, 2.5, & 1.25)

In [20]:
fig = plt.figure(figsize = (8,8))
m = Basemap(projection='cyl',llcrnrlon=32.5,llcrnrlat=3,urcrnrlon=49,urcrnrlat=15, resolution = 'i')
m.drawlsmask(land_color = "#ddaa66", ocean_color="#7777ff", resolution = 'i', lakes=True, grid=1.25)
m.drawcountries(linewidth=1, linestyle='solid', color='k' ) 
plt.title("Land-sea mask image", fontsize=20)
plt.show()

NASA Blue Marble image¶

  • Use the bluemarble() argument to apply the NASA blue marble image as a background map

  • To downgrade or upgrade image resolution use the scale argument

In [21]:
fig = plt.figure(figsize = (8,8))
m = Basemap(projection='cyl',llcrnrlon=32.5,llcrnrlat=3,urcrnrlon=49,urcrnrlat=15, resolution='i')
m.bluemarble(scale=1.0)
m.drawcoastlines()
m.drawcountries(linewidth=1, linestyle='solid', color='k' ) 
plt.title("NASA Blue Marble image as background map", fontsize=18)
Out[21]:
Text(0.5, 1.0, 'NASA Blue Marble image as background map')

Shaded relief image¶

Use shadedrelief() argument to apply shaded relief image as a background map

In [22]:
fig = plt.figure(figsize = (8,8))
m = Basemap(projection='cyl',llcrnrlon=32.5,llcrnrlat=3,urcrnrlon=49,urcrnrlat=15, resolution='i')
m.shadedrelief()
m.drawcoastlines()
m.drawcountries(linewidth=1, linestyle='solid', color='k' ) 
plt.title("Shaded relief image as background map", fontsize=18)
Out[22]:
Text(0.5, 1.0, 'Shaded relief image as background map')

NOAAetopo relief image¶

Use etopo() argument to apply shaded relief image as a background map

In [23]:
fig = plt.figure(figsize = (8,8))
m = Basemap(projection='cyl',llcrnrlon=32.5,llcrnrlat=3,urcrnrlon=49,urcrnrlat=15, resolution='i')
m.etopo(scale=1.2)
m.drawcoastlines()
m.drawcountries(linewidth=1, linestyle='solid', color='k' ) 
plt.title("Shaded relief image as background map", fontsize=18)
Out[23]:
Text(0.5, 1.0, 'Shaded relief image as background map')

Plotting netCDF data using Basemap¶

Reading ECMWF temperature data¶

To read the netcdf data, we’ll use the Dataset class from the netcdf4-python library

In [24]:
from netCDF4 import Dataset as dataset
In [25]:
nc = dataset('ECMWF_temp2m.nc')
In [26]:
nc.dimensions
Out[26]:
{'longitude': <class 'netCDF4._netCDF4.Dimension'>: name = 'longitude', size = 144,
 'latitude': <class 'netCDF4._netCDF4.Dimension'>: name = 'latitude', size = 73,
 'time': <class 'netCDF4._netCDF4.Dimension'>: name = 'time', size = 62}
In [27]:
nc.variables
Out[27]:
{'longitude': <class 'netCDF4._netCDF4.Variable'>
 float32 longitude(longitude)
     _FillValue: nan
     units: degrees_east
     long_name: longitude
 unlimited dimensions: 
 current shape = (144,)
 filling on,
 'latitude': <class 'netCDF4._netCDF4.Variable'>
 float32 latitude(latitude)
     _FillValue: nan
     units: degrees_north
     long_name: latitude
 unlimited dimensions: 
 current shape = (73,)
 filling on,
 'time': <class 'netCDF4._netCDF4.Variable'>
 int32 time(time)
     long_name: time
     units: hours since 1900-01-01
     calendar: proleptic_gregorian
 unlimited dimensions: 
 current shape = (62,)
 filling on, default _FillValue of -2147483647 used,
 'p2t': <class 'netCDF4._netCDF4.Variable'>
 int16 p2t(time, latitude, longitude)
     _FillValue: -32767
     units: K
     long_name: 2 metre temperature
     add_offset: 262.39847874753474
     scale_factor: 0.0018355835199370632
     missing_value: -32767
 unlimited dimensions: 
 current shape = (62, 73, 144)
 filling on}
  • Read the coordinate variables
  • latitude
  • longitude
  • time
  • data variable (2-meter temperature)
In [28]:
lat = nc.variables['latitude'][:]
lon = nc.variables['longitude'][:]
time = nc.variables['time'][:]
t2 = nc.variables['p2t'][:]

Plotting filled contour maps¶

  • Use the contourf() function to draw filled contour maps

  • Create a 2D meshgridmatrix from 1D longitude & latitude arrays

  • contourf() function mainly takes:

    • longitude & latitude arrays
    • data
    • colormap
    • levels
In [29]:
fig = plt.figure(num=None, figsize=(8, 8)) 

m = Basemap(projection='cyl', llcrnrlon=32.5, llcrnrlat=3, urcrnrlon=49, urcrnrlat=15, resolution='i')
x, y = m(*np.meshgrid(lon,lat))

cs = m.contourf(x, y ,np.squeeze(t2[0,:,:]), levels = 50, cmap=plt.cm.jet)

m.drawcoastlines()
m.drawmapboundary()
m.drawcountries(linewidth=1, linestyle='solid', color='k' ) 

m.drawmeridians(range(33, 48, 2), color='k', linewidth=1.0, dashes=[4, 4], labels=[0, 0, 0, 1])
m.drawparallels(range(3, 15, 2), color='k', linewidth=1.0, dashes=[4, 4], labels=[1, 0, 0, 0])

plt.ylabel("Latitude", fontsize=15, labelpad=35)
plt.xlabel("Longitude", fontsize=15, labelpad=20)

cbar = m.colorbar(cs, location='right', pad="3%")
cbar.set_label('Temperature (K)', fontsize=13)

plt.title('2-meter temperature filled contour map', fontsize=15)
plt.show()

Plotting contour maps¶

  • Use the contour() function to draw contour maps.

  • contour() function uses similar arguments like contourf()

In [30]:
fig = plt.figure(num=None, figsize=(8, 8)) 

m = Basemap(projection='cyl', llcrnrlon=32.5, llcrnrlat=3, urcrnrlon=49, urcrnrlat=15, resolution='i')

x, y = m(*np.meshgrid(lon,lat))

cs = m.contour(x, y ,np.squeeze(t2[4,:,:]), levels = 25 ,cmap=plt.cm.jet)

m.drawcoastlines()
m.drawmapboundary()
m.drawcountries(linewidth=1, linestyle='solid', color='k' ) 

m.drawmeridians(range(33, 48, 2), color='k', linewidth=1.0, dashes=[4, 4], labels=[0, 0, 0, 1])
m.drawparallels(range(3, 15, 2), color='k', linewidth=1.0, dashes=[4, 4], labels=[1, 0, 0, 0])

plt.ylabel("Latitude", fontsize=15, labelpad=35)
plt.xlabel("Longitude", fontsize=15, labelpad=20)

cbar = m.colorbar(cs, location='right', pad="3%")
cbar.set_label('Temperature (K)', fontsize=13)

plt.clabel(cs, inline=True, fmt='%1.0f', fontsize=12, colors='k')
plt.title('2-meter temperature contour map', fontsize=15)
plt.show()
In [31]:
fig = plt.figure(num=None, figsize=(8, 8)) 

m = Basemap(projection='cyl', llcrnrlon=32.5, llcrnrlat=3, urcrnrlon=49, urcrnrlat=15, resolution='i')

x, y = m(*np.meshgrid(lon,lat))

clevs = np.arange(295, 321, 3)
#clevs = [295, 297, 299, 301, 303, 305, 307, 309, 311, 3315, 320]

cs = m.contour(x, y ,np.squeeze(t2[4,:,:]), clevs ,cmap=plt.cm.jet)

m.drawcoastlines()
m.drawmapboundary()
m.drawcountries(linewidth=1, linestyle='solid', color='k' ) 

m.drawmeridians(range(33, 48, 2), color='k', linewidth=1.0, dashes=[4, 4], labels=[0, 0, 0, 1])
m.drawparallels(range(3, 15, 2), color='k', linewidth=1.0, dashes=[4, 4], labels=[1, 0, 0, 0])

plt.ylabel("Latitude", fontsize=15, labelpad=35)
plt.xlabel("Longitude", fontsize=15, labelpad=20)

cbar = m.colorbar(cs, location='right', pad="3%")
cbar.set_label('Temperature (K)', fontsize=13)

plt.clabel(cs, inline=True, fmt='%1.0f', fontsize=12, colors='k')
plt.title('2-meter temperature contour map', fontsize=15)
plt.show()

Plotting pseudo color maps¶

Use the pcolor() or pcolormesh() function to draw pseudo color maps

In [32]:
fig = plt.figure(figsize=(8, 8) ) 

m = Basemap(projection='cyl', llcrnrlon=32.5, llcrnrlat=3, urcrnrlon=49, urcrnrlat=15, resolution='i')

# cs = m.pcolor(x, y ,np.squeeze(t2[4,:,:]))
cs = m.pcolormesh(x, y ,np.squeeze(t2[4,:,:]))

# pcolor(): draw a pseudocolor plot.
# pcolormesh(): draw a pseudocolor plot (faster version for regular meshes).

m.drawmeridians(range(33, 48, 2), color='k', linewidth=1.0, dashes=[4, 4], labels=[0, 0, 0, 1])
m.drawparallels(range(3, 15, 2), color='k', linewidth=1.0, dashes=[4, 4], labels=[1, 0, 0, 0])

m.drawcoastlines()
m.drawmapboundary()
m.drawcountries(linewidth=1, linestyle='solid', color='k' ) 

plt.ylabel("Latitude", fontsize=15, labelpad=35)
plt.xlabel("Longitude", fontsize=15, labelpad=20)

cbar = m.colorbar(cs, location='right', pad="3%")
cbar.set_label('Temperature (K)', fontsize=13)

plt.title('2-meter temperature pseudo-color map', fontsize=15)
plt.show()

Plot data points¶

In [33]:
# Define the data points
latitudes = [10.90, 3.82, 6.60, 12.68, 8.09, 12.51, 14.21, 11.38, 4.19, 13.33]
longitudes = [34.41, 36.36, 40.55, 47.89, 44.39, 44.13, 44.9, 40.36, 39.14, 47.05]
data = [200, 150, 175, 189, 100, 315, 222, 275, 155, 190]
In [34]:
fig = plt.figure(figsize=(8, 8) ) 

# Create a Basemap instance
m = Basemap(
    llcrnrlon=33, llcrnrlat=3, urcrnrlon=48, urcrnrlat=15,
    projection='merc', resolution='i')

# Draw coastlines, countries, and states
m.drawcoastlines(linewidth=0.5)
m.drawcountries(linewidth=0.5)
m.drawstates(linewidth=0.5)

# Draw parallels and meridians
m.drawparallels(np.arange(0, 90, 4), labels=[1,0,0,0], fontsize=10)
m.drawmeridians(np.arange(-180, 180, 4), labels=[0,0,0,1], fontsize=10)

# Convert latitudes and longitudes to map coordinates
x, y = m(longitudes, latitudes)

# Plot the data points as markers on the map
m.scatter(x, y, c=data, cmap='cool', s=80, edgecolors='k', linewidths=0.5)

# Add a colorbar
plt.colorbar(label='Data', shrink =0.5)

# Add a title
plt.title('Data Points')

# Show the plot
plt.show()
In [ ]:
In [35]:
fig = plt.figure(figsize=(8, 8) ) 


# Define the data points
latitudes = [10.90, 3.82, 6.60, 12.68, 8.09, 12.51, 14.21, 11.38, 4.19, 13.33]
longitudes = [34.41, 36.36, 40.55, 47.89, 44.39, 44.13, 44.9, 40.36, 39.14, 47.05]
data = [200, 150, 175, 189, 100, 315, 222, 275, 155, 190]

# Create a Basemap instance
m = Basemap(
    llcrnrlon=33, llcrnrlat=3, urcrnrlon=48, urcrnrlat=15,
    projection='merc', resolution='i'
)

# Draw coastlines, countries, and states
m.drawcoastlines(linewidth=0.5)
m.drawcountries(linewidth=0.5)
m.drawstates(linewidth=0.5)

# Draw parallels and meridians
m.drawparallels(np.arange(0, 90, 5), labels=[1,0,0,0], fontsize=10)
m.drawmeridians(np.arange(-180, 180, 5), labels=[0,0,0,1], fontsize=10)

# Convert latitudes and longitudes to map coordinates
x, y = m(longitudes, latitudes)

# Plot the data points as markers on the map
m.scatter(x, y, c=data, cmap='cool', s=100, edgecolors='k', linewidths=0.5)

# Add labels to the data points
for i in range(len(latitudes)):
    plt.text(x[i]+50000, y[i]+50000, str(data[i]), fontsize=10, fontweight='bold', ha='center', va='center')

# Add a colorbar
plt.colorbar(label='Data', shrink = 0.5)

# Add a title
plt.title('Data Points Labled ')

# Show the plot
plt.show()
In [ ]: